Plasma lensing with magnetic field and a small correction to the Faraday rotation measurement

Plasma lensing displays interesting characteristics that set it apart from gravitational lensing. The magnetised medium induces birefringence in the two polarisation modes. As the lensing deflection grows stronger, e.g. when images form near the critical curve, the geometric delay of the signal can cause rotation in linear polarisation, in addition to Faraday rotation. This rotation has a frequency dependence to the power of four. We study the geometric rotation of the lensed image in a Gaussian density model and find that it is necessary to take into account the geometric rotation when estimating magnetised media, especially in the under-dense lens. At frequencies of $\sim 1$ GHz or lower, the geometric rotation can dominate. We simulate the flux of lensed images and find that when the image forms near the lensing critical curve, the birefringence can convert the linear polarisation and un-polarisation pulse into a circular mode. The lensing magnification has the potential to increase the probability of detecting such events.Comment: MNRAS, 7 pages, comments welcom

Prospects for Detecting Fast Radio Bursts in Globular Clusters of Nearby Galaxies

The recent detection of a repeating fast radio burst (FRB) in an old globular cluster in M81 challenges traditional FRB formation mechanisms based on magnetic activity in young neutron stars formed recently in core-collapse supernovae. Furthermore, the detection of this repeater in such a nearby galaxy implies a high local universe rate of similar events in globular clusters. Building off the properties inferred from the M81 FRB, we predict the number of FRB sources in nearby ($d \lesssim 20\,$Mpc) galaxies with large globular cluster systems known. Incorporating the uncertain burst energy distribution, we estimate the rate of bursts detectable in these galaxies by radio instruments such as FAST and MeerKat. Of all local galaxies, we find M87 is the best candidate for FRB detections. We predict M87's globular cluster system contains $\mathcal{O}(10)$ FRB sources at present and that a dedicated radio survey (by FAST or MeerKat) of $\mathcal{O}(10)\,$hr has a $90\%$ probability of detecting a globular cluster FRB in M87. The detection of even a handful of additional globular cluster FRBs would provide invaluable constraints on FRB mechanisms and population properties. Previous studies have demonstrated young neutron stars formed following collapse of dynamically-formed massive white dwarf binary mergers may provide the most natural mechanism for these bursts. We explore the white dwarf merger scenario using a suite of $N$-body cluster models, focusing in particular on such mergers in M87 clusters. We describe a number of outstanding features of this scenario that in principle may be testable with an ensemble of observed FRBs in nearby globular clusters.Comment: 22 pages, 9 figures, 2 tables. Accepted for publication in Ap

Skeleton-Based Gesture Recognition With Learnable Paths and Signature Features

For the skeleton-based gesture recognition, graph convolutional networks (GCNs) have achieved remarkable performance since the human skeleton is a natural graph. However, the biological structure might not be the crucial one for motion analysis. Also, spatial differential information like joint distance and angle between bones may be overlooked during the graph convolution. In this paper, we focus on obtaining meaningful joint groups and extracting their discriminative features by the path signature (PS) theory. Firstly, to characterize the constraints and dependencies of various joints, we propose three types of paths, i.e., spatial, temporal, and learnable path. Especially, a learnable path generation mechanism can group joints together that are not directly connected or far away, according to their kinematic characteristic. Secondly, to obtain informative and compact features, a deep integration of PS with few parameters are introduced. All the computational process is packed into two modules, i.e., spatial-temporal path signature module (ST-PSM) and learnable path signature module (L-PSM) for the convenience of utilization. They are plug-and-play modules available for any neural network like CNNs and GCNs to enhance the feature extraction ability. Extensive experiments have conducted on three mainstream datasets (ChaLearn 2013, ChaLearn 2016, and AUTSL). We achieved the state-of-the-art results with simpler framework and much smaller model size. By inserting our two modules into the several GCN-based networks, we can observe clear improvements demonstrating the great effectiveness of our proposed method

Detection of 15 bursts from FRB 180916.J0158+65 with the uGMRT

We report the findings of a uGMRT observing campaign on FRB 180916.J0158+65, discovered recently to show a 16.35-day periodicity of its active cycle. We observed the source at 550-750 MHz for $\sim 2$ hours each during three successive cycles at the peak of its expected active period. We find 0, 12, and 3 bursts respectively, implying a highly variable bursting rate even within the active phase. We consistently detect faint bursts with spectral energies only an order of magnitude higher than the Galactic burst source SGR~1935+2154. The times of arrival of the detected bursts rule out many possible aliased solutions, strengthening the findings of the 16.35-day periodicity. A short-timescale periodicity search returned no highly significant candidates. Two of the beamformer-detected bursts were bright enough to be clearly detected in the imaging data, achieving sub-arcsecond localization, and proving as a proof-of-concept for FRB imaging with the GMRT. We provide a $3\sigma$ upper limit of the persistent radio flux density at 650 MHz of $66~\mu{\rm Jy}$ which, combined with the EVN and VLA limits at 1.6~GHz, further constrains any potential radio counterpart. These results demonstrate the power of uGMRT for targeted observations to detect and localize known repeating FRBs.Comment: 5 pages, 4 figures, accepted for publication in MNRAS Letter